- We present a connectionist model that combines motions and language based on the behavioral experiences of a real robot. Two models of recurrent neural network with parametric bi...
Tetsuya Ogata, Masamitsu Murase, Jun Tani, Kazunor...
We experimented on task-level robot learning based on bi-directional theory. The via-point representation was used for ‘learning by watching’. In our previous work, we had a r...
This paper is about the design of an artificial neural network to control an autonomous robot that is required to iteratively solve a discrimination task based on time-dependent s...
— Despite the many significant advances made in robotics research, few works have focused on the tight integration of task planning and motion control. Most integration works in...
The paper examines characteristics of interactive learning between human tutors and a robot having a dynamic neural network model which is inspired by human parietal cortex functio...
Jun Tani, Ryunosuke Nishimoto, Jun Namikawa, Masat...